Developing RAG Applications with LlamaIndex and Gen AI Online Course
Developing RAG Applications with LlamaIndex and Gen AI Online Course
This course provides an in-depth introduction to Large Language Models (LLMs) with a focus on LlamaIndex. You will begin by setting up your development environment and creating your first program, exploring advanced prompt techniques. As you advance, you'll dive deeper into LlamaIndex, learning to format prompt templates, design conversational prompts, and apply semantic similarity evaluators. Key concepts like language embeddings and vector databases will be covered, including integration with SQL and Chroma DB. You'll also learn how to create efficient query pipelines such as sequential, DAG, and dataframe pipelines. Practical projects will include building a calculator with a ReAct agent, developing a dynamic document agent, and creating a code checker UI with Streamlit, equipping you with hands-on experience for real-world AI application development.
Key Benefits
- Thorough walkthrough of LlamaIndex setup and its practical applications
- Master advanced prompt engineering strategies for enhanced functionality
- Seamless integration with SQL and Chroma DB vector databases for efficient data management
Target Audience
This course is for intermediate to advanced developers and AI enthusiasts who possess a foundational understanding of Python programming and machine learning principles. While prior knowledge of Large Language Models (LLMs) and natural language processing (NLP) will be advantageous, it is not a prerequisite for participation.
Learning Objectives
- Develop and implement programs using LlamaIndex
- Design and leverage advanced prompt templates for enhanced functionality
- Effectively evaluate and apply semantic similarity techniques
- Integrate LlamaIndex with multiple database systems for efficient data handling
- Set up, configure, and optimize various query pipelines for robust performance
- Create dynamic agents and tools to enhance AI application development and automation
Course Outline
The Developing RAG Applications with LlamaIndex and Gen AI Exam covers the following topics -
Module 1 - Course Overview
- Introduction to the Course
- Understanding Large Language Models (LLMs)
- Overview of LlamaIndex Framework
- Fundamentals of Prompt Engineering
- Advanced Prompt Techniques
- Setting Up Your Development Environment
- First Program Using LlamaIndex
Module 2 - Deep Dive into LlamaIndex
- Creating and Structuring Prompt Templates
- Designing Conversational Prompts
- Evaluating Semantic Similarity
- Working with Language Embeddings and Vector Databases
- Integrating Chroma DB Vector Database
- Connecting LlamaIndex with SQL Databases
- Constructing LlamaIndex Query Pipelines
- Configuring a Basic Sequential Query Pipeline
- Building a Directed Acyclic Graph (DAG) Pipeline
- Developing a Dataframe Pipeline
- Utilizing Agents and Tools for Dynamic Processing
- Implementing a ReAct Agent to Build a Calculator
- Creating a Document Agent with Dynamic Tool Generation
- Developing a Code Checker Using Streamlit UI
